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Query hourly search analytics

query_hourly_analytics

Read-only

Breaks down Google Search performance by hour (Pacific Time) for the last ~10 days, helping spot same-day spikes or compare today with the same day last week.

Instructions

Search performance broken down by hour (Pacific Time) for the last ~10 days. Use it to spot same-day spikes or compare today with the same day last week. The most recent hours are incomplete; first_incomplete_hour says where that starts.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`filters`	No	Filters, combined with AND.
`end_date`	No	Last day, YYYY-MM-DD in Pacific Time. Defaults to today.
`site_url`	Yes	The property, as listed by list_sites: 'sc-domain:example.com' for a domain property or 'https://www.example.com/' for a URL-prefix property. A bare domain such as 'example.com', or any URL on the site, is resolved to the property that contains it.
`row_limit`	No	Rows to return (1-25,000).
`start_row`	No	Zero-based row offset, for paging.
`dimensions`	No	Extra grouping besides the hour. Omit for hourly totals.
`start_date`	No	First day, YYYY-MM-DD in Pacific Time, within the last 10 days. Defaults to 2 days ago.
`search_type`	No		web

Output Schema

TableJSON Schema

Name	Required	Description
`rows`	Yes	One object per row: dimension values by name, then clicks, impressions, ctr (0-1) and position (absent for Discover and Google News).
`notes`	No
`request`	Yes	The exact request body sent to Google.
`end_date`	Yes
`site_url`	Yes
`row_count`	Yes
`data_state`	Yes
`dimensions`	Yes
`start_date`	Yes
`search_type`	Yes
`next_start_row`	No	Pass as start_row to fetch the next page, if there is one.
`aggregation_type`	No
`first_incomplete_date`	No
`first_incomplete_hour`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.4.0Oct 15, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely useful behavior the annotations lack: results are in Pacific Time, capped at ~10 days, and recent hours are incomplete with first_incomplete_hour marking the boundary.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with the scope, then the use case, then the data-freshness caveat. Every sentence earns its place with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and annotations covering the safety profile, the description only needs to add the time/window/freshness context, which it does. It could say slightly more about how the dimensions parameter interacts with hourly grouping, but that gap is minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 88%, so the schema documents parameters itself. The description reinforces the 10-day window that constrains start_date but adds no per-parameter syntax or semantics beyond what the schema and its enum/description already provide. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (query) and resource (hourly search analytics) with the exact granularity (per hour), timezone (Pacific Time), and window (~10 days). This distinguishes it from the daily-grain sibling query_search_analytics without needing to open either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit usage contexts: spotting same-day spikes and comparing today to the same day last week. Clear when-to-use guidance, but it never names the alternative tool (e.g. query_search_analytics) to steer the agent away when daily granularity suffices.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.